• Journal of Integrative Natural Science
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• v.5 no.1
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• pp.6-12
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• 2012

c-Jun N-terminal kinase-3 (JNK-3) has been identified as a promising target for neuronal apoptosis and has the effective therapeutic for neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and other CNS disorders. Herein, we report the essential structural and chemical parameters for JNK-3 inhibitors utilizing comparative molecular field similarity indices analysis (CoMSIA) using the derivatives of 3,5-disubstituted quinolines. The best predictions were obtained CoMSIA model (q2=0.834, r2=0.987) and the statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The resulting contour map from 3D-QSAR models might be helpful to design novel and more potent JNK3 derivatives.

• Analytical Science and Technology
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• v.34 no.2
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• pp.46-55
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• 2021

Evaluation of drug-excipient compatibility is one of the basic steps in the preformulation of pharmaceutical dosage forms. Some reactive excipients have been known so far which may cause stability problems for drug molecules in pharmaceutical dosage forms. The aim of this study was to evaluate drugexcipient compatibility of gliclazide with some common pharmaceutical excipients, known for their ability to incorporate in drug-excipient interactions. Binary mixtures were prepared using lactose, magnesium stearate, polyvinylpyrrolidone, sodium starch glycolate, polyethylene glycol 2000 and dicalcium phosphate. Based on the results; gliclazide was incompatible with all tested excipients; but not with dicalcium phosphate. DSC (Differential Scanning Calorimetry) results were in accordance with HPLC (High Pressure liquid chromatography) data and were more predictive than FTIR (Fourier Transform Infrared Spectroscopy). Drug and reactive excipients incompatibility was fully discussed and documented. It is advisable to avoid incompatible excipients or carefully monitor the drug stability when incorporating such excipients in final formulation designs.

• Structural Engineering and Mechanics
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• v.87 no.6
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• pp.601-614
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• 2023

In this study, the uniaxial ratcheting effect of Z2CND18.12N austenitic stainless steel at room and elevated temperatures is firstly simulated based on the Ahmadzadeh-Varvani hardening rule (A-V model), which is embedded into the finite element software ABAQUS by writing the user material subroutine UMAT. The results show that the predicted results of A-V model are lower than the experimental data, and the A-V model is difficult to control ratcheting strain rate. In order to improve the predictive ability of the A-V model, the parameter γ2 of the A-V model is modified using the isotropic hardening criterion, and the extended A-V model is proposed. Comparing the predicted results of the above two models with the experimental data, it is shown that the prediction results of the extended A-V model are in good agreement with the experimental data.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.989-998
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• 2023

Under nuclear reactor severe accidents, the resuspension of radioactive aerosol may occur in the containment due to the disturbing airflow generated by hydrogen combustion, hydrogen explosion and containment depressurization resulting in the increase of radioactive source term in the containment. In this paper, for containment conditions, by considering the contact between particle and rough deposition surface, the distribution of the distance between two contact points of particle and deposition surface, rolling and lifting separation mechanism, resuspension model based on random contact with rough surface (RRCR) is established. Subsequently, the detailed torque and force analysis is carried out, which indicates that particles are more easily resuspended by rolling under low disturbing airflow velocity. The simulation result is compared with the experimental result and the prediction of different simulation methods, the RRCR model shows equivalent and better predictive ability, which can be applicable for simulation of aerosol resuspension in containment during severe accident.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.176-176
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• 2021

한반도의 강수를 예측하는 것은 수자원 관리 측면에서 매우 중요하다. 한반도의 강수는 연별 변동 뿐 아니라 계절별로 변동을 갖는다. 우리는 이 중 건기(Dry period)의 가뭄과 그 이후 농번기(3월, 4월)에 영향을 미치는 초겨울(11월, 12월)의 강수를 예측은 수자원 관리에 있어서 중요한 의미를 갖는다. 본 연구에서는 Regularized regression 모형인 Elastic net model을 이용하여 중장기 (7개월 이상)기반으로 초겨울의 강우 예측의 가능성에 대해서 논하고자 한다. 특히, 본 연구에서는 우리나라의 초겨울 강우의 변동이 대서양의 대규모의 대기 순환과 밀접한 관계를 보이는 것을 확인하였으며 이를 논하기 위해서 Sea Surface Temperature (SST) 등의 자료를 사용하여 분석하였다. 이 시간적 지체 효과를 갖고 있는 대기 순환은 Eurasia 지역을 기반으로 횡적인 순환과 관련이 깊은 것으로 파악되었다. 본 연구의 결과는 앞으로 우리나라의 가뭄관리에 유용하게 활용될 것으로 기대된다.

• The Journal of Information Systems
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• v.33 no.1
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• pp.31-44
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• 2024

Purpose The purpose of this study is to use climate data to find the algorithm with the highest Hallabong production prediction ability and to predict future Hallabong production in areas where Hallabong cultivation is expected to be possible. Design/methodology/approach The research is conducted in two stages. In the first step, find the algorithm with the highest predictive power among XGBoost, Random Forest, SVM, and LSTM methodologies. In the second stage, the algorithm found in the first stage is applied to predict future Hallabong production in three regions where Hallabong production is expected to be possible. Findings As with many prediction studies, we found that XGBoost showed the highest prediction power. Even in areas where Hallabong production is expected to be possible, Hallabong production was predicted to be highest in Hongcheon, Gangwon-do, which has the highest latitude.

• Journal of Korean Academy of Nursing
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• v.42 no.3
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• pp.434-442
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• 2012

Purpose: The purpose of this predictive study was to identify factors affecting health related quality of life (HRQoL) in patients with rheumatoid arthritis (RA). Methods: The participants in this study were 131 patients with RA who were recruited from the outpatient clinic of a university hospital in Seoul. Disease activity in rheumatoid arthritis was evaluated by calculating the Disease Activity Score 28. Disability in activities of daily living (ADL) was assessed with the Korean Health Assessment Questionnaire, and depression with The Center for Epidemiologic Studies Depression Scale. HRQoL was evaluated using The Short Form 36 Health Survey. Data were analyzed using descriptive statistics, correlation, and hierarchical multiple regression. Results: Pain, disability in ADL, disease activity, and depression correlated negatively with physical and mental dimensions of HRQoL. But hierachical multiple regression analysis revealed that disability in ADL and depression were the only variables negatively influencing physical and mental QoL after adjustment for influences of sociodemographic variables. Conclusion: Results of this study suggest that disability in ADL and depression, rather than disease activity and pain have profound effects on HRQoL in patients with RA. Further studies are needed to assess the predictive ability of disease activity and pain on HRQoL in this population.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5571-5575
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• 2014

Background: The ability to predict the survival time of breast cancer patients is important because of the potential high morbidity and mortality associated with the disease. To develop a predictive inference for determining the survival of breast cancer patients, we applied a novel Bayesian method. In this paper, we propose the development of a databased statistical probability model and application of the Bayesian method to predict future survival times for White Hispanic female breast cancer patients, diagnosed in the US during 1973-2009. Materials and Methods: A stratified random sample of White Hispanic female patient survival data was selected from the Surveillance Epidemiology and End Results (SEER) database to derive statistical probability models. Four were considered to identify the best-fit model. We used three standard model-building criteria, which included Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) to measure the goodness of fit. Furthermore, the Bayesian method was used to derive future survival inferences for survival times. Results: The highest number of White Hispanic female breast cancer patients in this sample was from New Mexico and the lowest from Hawaii. The mean (SD) age at diagnosis (years) was 58.2 (14.2). The mean (SD) of survival time (months) for White Hispanic females was 72.7 (32.2). We found that the exponentiated Weibull model best fit the survival times compared to other widely known statistical probability models. The predictive inference for future survival times is presented using the Bayesian method. Conclusions: The findings are significant for treatment planning and health-care cost allocation. They should also contribute to further research on breast cancer survival issues.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.61-69
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• 2020

The uniaxial compressive strength (UCS) of rock is a basic parameter in underground engineering design. The disadvantages of this commonly employed laboratory testing method are untimely testing, difficulty in performing core testing of broken rock mass and long and complicated onsite testing processes. Therefore, the development of a fast and simple in situ rock UCS testing method for field use is urgent. In this study, a multi-function digital rock drilling and testing system and a digital core bit dedicated to the system are independently developed and employed in digital drilling tests on rock specimens with different strengths. The energy analysis is performed during rock cutting to estimate the energy consumed by the drill bit to remove a unit volume of rock. Two quantitative relationship models of energy analysis-based core drilling parameters (ECD) and rock UCS (ECD-UCS models) are established in this manuscript by the methods of regression analysis and support vector machine (SVM). The predictive abilities of the two models are comparatively analysed. The results show that the mean value of relative difference between the predicted rock UCS values and the UCS values measured by the laboratory uniaxial compression test in the prediction set are 3.76 MPa and 4.30 MPa, respectively, and the standard deviations are 2.08 MPa and 4.14 MPa, respectively. The regression analysis-based ECD-UCS model has a more stable predictive ability. The energy analysis-based rock drilling method for the prediction of UCS is proposed. This method realized the quick and convenient in situ test of rock UCS.

• Journal of Periodontal and Implant Science
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• v.46 no.1
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• pp.10-21
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• 2016

Purpose: This study evaluated the predictive performance of a combination of self-report questionnaires, salivary hemoglobin levels, and age as a non-invasive screening method for periodontitis. Methods: The periodontitis status of 202 adults was examined using salivary hemoglobin levels, responses to 10 questions on a self-report questionnaire, and the Community Periodontal Index (CPI). The ability of those two variables and the combination thereof with age to predict the presence of CPI scores of 3-4 and 4 was assessed using logistic regression and receiver operating characteristic (ROC) curve analysis. Results: CPI scores of 3-4 and 4 were present among 79.7% and 46.5% of the sample, respectively. The area under the ROC curves (AUROCs) of salivary hemoglobin levels for predicting prevalence of CPI scores of 3-4 and 4 were 0.63 and 0.67, respectively (with sensitivity values of 71% and 60% and specificity values of 56% and 72%, respectively). Two distinct sets of five questions were associated with CPI scores of 3-4 and 4, with AUROCs of 0.73 and 0.71, sensitivity values of 76% and 66%, and specificity values of 63% and 69%. The combined model incorporating both variables and age showed the best predictive performance, with AUROCs of 0.78 and 0.76, sensitivity values of 71% and 65%, and specificity values of 68% and 77% for CPI scores of 3-4 and 4, respectively. Conclusions: The combination of salivary hemoglobin levels and self-report questionnaires was shown to be a valuable screening method for detecting periodontitis.